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Abstract
Background: Walking is the most common form of physical activity (PA) among U.S. adults, and is the most popular choice of aerobic PA to improve overall health. Although walking has received increased attention in recent years as an important means to improve population health, more than half of U.S. adults do not get the amount of aerobic PA recommended for health benefits and approximately one third are entirely inactive.
Purpose: The purpose of this study was to quantify objectively measured walking bouts that occurred within the home neighborhood, and to examine the association between the number of walking bouts in the home neighborhood and neighborhood-level walkability.
Methods: This cross-sectional study involved 106 individual twins from the University of Washington Twin Registry who were participated in a larger, funded study. For the present study, accelerometer and GPS data were collected from each subject for two weeks for the purpose of quantifying walking bouts. The walking bouts were quantified within 1-, 2-, and 3-km straight-line and network home neighborhood buffers. A neighborhood walkability score was calculated using a commercially available algorithm (Walk Score® ), which uses data from business listings, road networks, schools, and public transit derived from multiple sources to map the walking distance to amenities in nine different categories (e.g., schools, parks, restaurants, etc.), with each category weighted by importance. Mixed effect models were used to test for associations, which controlled for age, sex, body mass index, and annual income level.
Result: A total of 514 walking bouts were identified from 1464 person-days. On average, participants had 2.5 walking bouts per week, and each bout lasted 12 minutes. More walking bouts were quantified within straight-line buffers than network buffers of the same distance, and the counts of within-neighborhood walking bouts increased with buffer distance for both buffer types. A significant positive association was found between neighborhood walkability scores and the numbers of walking bouts within all neighborhood buffers (p<0.01); the counts within 2-km straight-line and 3-km network buffers showed the strongest association with neighborhood walkability.
Conclusion: Quantification of walking episodes within and outside of pre-defined neighborhood buffers of different scales and types specifies the locations for walking and allows us to better describe and elucidate walking behaviors. Furthermore, the walkability of the home neighborhood was associated with walking activity, providing insight into the effects of neighborhood environment features on walking behaviors among adults.
